Prediction of the optimized welding parameters for the joined brass plates using genetic algorithm

Welding is a major bonding technique in the industry. The importance of welding directed many researches to search how well welding can be obtained. Three main indicators, such as welding current (A), welding velocity (v) and arc length (b), have a big influence in the quality welding. Since all these factors affect the quality of the welded joining parts, the effect of these parameters was investigated experimentally. The present paper describes the use of stochastic search process that is the basis of genetic algorithms (GAs), in developing estimation of the welding parameters for the joined brass plates. Developed models having non-linear estimation models using GA techniques are validated with actual data. Genetic Algorithm Welding Current Estimation Model and Genetic Algorithm Welding Velocity Estimation Model are used to estimate the welding current and velocity according to the welding environment for the brass material.